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An important goal in biotechnology and (bio-) medical research is the isolation of single cells from a heterogeneous cell population. These specialised cells are of great interest for bioproduction, diagnostics, drug development, (cancer) therapy and research. To tackle emerging questions, an ever finer differentiation between target cells and non-target cells is required. This precise differentiation is a challenge for a growing number of available methods.
Since the physiological properties of the cells are closely linked to their morphology, it is beneficial to include their appearance in the sorting decision. For established methods, this represents a non addressable parameter, requiring new methods for the identification and isolation of target cells. Consequently, a variety of new flow-based methods have been developed and presented in recent years utilising 2D imaging data to identify target cells within a sample. As these methods aim for high throughput, the devices developed typically require highly complex fluid handling techniques, making them expensive while offering limited image quality.
In this work, a new continuous flow system for image-based cell sorting was developed that uses dielectrophoresis to precisely handle cells in a microchannel. Dielectrophoretic forces are exerted by inhomogeneous alternating electric fields on polarisable particles (here: cells). In the present system, the electric fields can be switched on and off precisely and quickly by a signal generator. In addition to the resulting simple and effective cell handling, the system is characterised by the outstanding quality of the image data generated and its compatibility with standard microscopes. These aspects result in low complexity, making it both affordable and user-friendly.
With the developed cell sorting system, cells could be sorted reliably and efficiently according to their cytosolic staining as well as morphological properties at different optical magnifications. The achieved purity of the target cell population was up to 95% and about 85% of the sorted cells could be recovered from the system. Good agreement was achieved between the results obtained and theoretical considerations. The achieved throughput of the system was up to 12,000 cells per hour. Cell viability studies indicated a high biocompatibility of the system.
The results presented demonstrate the potential of image-based cell sorting using dielectrophoresis. The outstanding image quality and highly precise yet gentle handling of the cells set the system apart from other technologies. This results in enormous potential for processing valuable and sensitive cell samples.
Search for light primordial black holes with VERITAS using gamma γ-ray and optical observations
(2023)
The Very Energetic Radiation Imaging Telescope Array System (VERITAS) is an array of four imaging atmospheric Cherenkov telescopes (IACTs). VERITAS is sensitive to very-high-energy gamma-rays in the range of 100 GeV to >30 TeV. Hypothesized primordial black holes (PBHs) are attractive targets for IACTs. If they exist, their potential cosmological impact reaches beyond the candidacy for constituents of dark matter. The sublunar mass window is the largest unconstrained range of PBH masses. This thesis aims to develop novel concepts searching for light PBHs with VERITAS. PBHs below the sublunar window lose mass due to Hawking radiation. They would evaporate at the end of their lifetime, leading to a short burst of gamma-rays. If PBHs formed at about 10^15 g, the evaporation would occur nowadays. Detecting these signals might not only confirm the existence of PBHs but also prove the theory of Hawking radiation. This thesis probes archival VERITAS data recorded between 2012 and 2021 for possible PBH signals. This work presents a new automatic approach to assess the quality of the VERITAS data. The array-trigger rate and far infrared temperature are well suited to identify periods with poor data quality. These are masked by time cuts to obtain a consistent and clean dataset which contains about 4222 hours. The PBH evaporations could occur at any location in the field of view or time within this data. Only a blind search can be performed to identify these short signals. This thesis implements a data-driven deep learning based method to search for short transient signals with VERITAS. It does not depend on the modelling of the effective area and radial acceptance. This work presents the first application of this method to actual observational IACT data. This thesis develops new concepts dealing with the specifics of the data and the transient detection method. These are reflected in the developed data preparation pipeline and search strategies. After correction for trial factors, no candidate PBH evaporation is found in the data. Thus, new constraints of the local rate of PBH evaporations are derived. At the 99% confidence limit it is below <1.07 * 10^5 pc^-3 yr^-1. This constraint with the new, independent analysis approach is in the range of existing limits for the evaporation rate.
This thesis also investigates an alternative novel approach to searching for PBHs with IACTs. Above the sublunar window, the PBH abundance is constrained by optical microlensing studies. The sampling speed, which is of order of minutes to hours for traditional optical telescopes, is a limiting factor in expanding the limits to lower masses. IACTs are also powerful instruments for fast transient optical astronomy with up to O(ns) sampling. This thesis investigates whether IACTs might constrain the sublunar window with optical microlensing observations. This study confirms that, in principle, the fast sampling speed might allow extending microlensing searches into the sublunar mass window. However, the limiting factor for IACTs is the modest sensitivity to detect changes in optical fluxes. This thesis presents the expected rate of detectable events for VERITAS as well as prospects of possible future next-generation IACTs. For VERITAS, the rate of detectable microlensing events in the sublunar range is ~10^-6 per year of observation time. The future prospects for a 100 times more sensitive instrument are at ~0.05 events per year.
Reliable and robust data processing is one of the hardest requirements for systems in fields such as medicine, security, automotive, aviation, and space, to prevent critical system failures caused by changes in operating or environmental conditions. In particular, Signal Integrity (SI) effects such as crosstalk may distort the signal information in sensitive mixed-signal designs. A challenge for hardware systems used in the space are radiation effects. Namely, Single Event Effects (SEEs) induced by high-energy particle hits may lead to faulty computation, corrupted configuration settings, undesired system behavior, or even total malfunction.
Since these applications require an extra effort in design and implementation, it is beneficial to master the standard cell design process and corresponding design flow methodologies optimized for such challenges. Especially for reliable, low-noise differential signaling logic such as Current Mode Logic (CML), a digital design flow is an orthogonal approach compared to traditional manual design. As a consequence, mandatory preliminary considerations need to be addressed in more detail. First of all, standard cell library concepts with suitable cell extensions for reliable systems and robust space applications have to be elaborated. Resulting design concepts at the cell level should enable the logical synthesis for differential logic design or improve the radiation-hardness. In parallel, the main objectives of the proposed cell architectures are to reduce the occupied area, power, and delay overhead. Second, a special setup for standard cell characterization is additionally required for a proper and accurate logic gate modeling. Last but not least, design methodologies for mandatory design flow stages such as logic synthesis and place and route need to be developed for the respective hardware systems to keep the reliability or the radiation-hardness at an acceptable level.
This Thesis proposes and investigates standard cell-based design methodologies and techniques for reliable and robust hardware systems implemented in a conventional semi-conductor technology. The focus of this work is on reliable differential logic design and robust radiation-hardening-by-design circuits. The synergistic connections of the digital design flow stages are systematically addressed for these two types of hardware systems. In more detail, a library for differential logic is extended with single-ended pseudo-gates for intermediate design steps to support the logic synthesis and layout generation with commercial Computer-Aided Design (CAD) tools. Special cell layouts are proposed to relax signal routing. A library set for space applications is similarly extended by novel Radiation-Hardening-by-Design (RHBD) Triple Modular Redundancy (TMR) cells, enabling a one fault correction. Therein, additional optimized architectures for glitch filter cells, robust scannable and self-correcting flip-flops, and clock-gates are proposed. The circuit concepts and the physical layout representation views of the differential logic gates and the RHBD cells are discussed. However, the quality of results of designs depends implicitly on the accuracy of the standard cell characterization which is examined for both types therefore. The entire design flow is elaborated from the hardware design description to the layout representations. A 2-Phase routing approach together with an intermediate design conversion step is proposed after the initial place and route stage for reliable, pure differential designs, whereas a special constraining for RHBD applications in a standard technology is presented.
The digital design flow for differential logic design is successfully demonstrated on a reliable differential bipolar CML application. A balanced routing result of its differential signal pairs is obtained by the proposed 2-Phase-routing approach. Moreover, the elaborated standard cell concepts and design methodology for RHBD circuits are applied to the digital part of a 7.5-15.5 MSPS 14-bit Analog-to-Digital Converter (ADC) and a complex microcontroller architecture. The ADC is implemented in an unhardened standard semiconductor technology and successfully verified by electrical measurements. The overhead of the proposed hardening approach is additionally evaluated by design exploration of the microcontroller application. Furthermore, the first obtained related measurement results of novel RHBD-∆TMR flip-flops show a radiation-tolerance up to a threshold Linear Energy Transfer (LET) of 46.1, 52.0, and 62.5 MeV cm2 mg-1 and savings in silicon area of 25-50 % for selected TMR standard cell candidates.
As a conclusion, the presented design concepts at the cell and library levels, as well as the design flow modifications are adaptable and transferable to other technology nodes. In particular, the design of hybrid solutions with integrated reliable differential logic modules together with robust radiation-tolerant circuit parts is enabled by the standard cell concepts and design methods proposed in this work.
The evolution of a galaxy is pivotally governed by its pattern of star formation over a given period of time. The star formation rate at any given time is strongly dependent on the amount of cold gas available in the galaxy. Accretion of pristine gas from the Intergalactic medium (IGM) is thought to be one of the primary sources for star-forming gas. This gas first passes through the virial regions of the galaxy before reaching the Interstellar medium (ISM), the hub of star formation. On the other hand, owing to the evolutionary course of young and massive stars, energetic winds are ejected from the ISM to the virial regions of the galaxy. A bunch of interlinked, complex astrophysical processes, arising from the concurrent presence of both infalling as well as outbound gas, play out over a range of timescales in the halo region or the Circumgalactic medium (CGM) of a galaxy. It would not be incorrect to say that the CGM has a stronghold over the gas reserves of a galaxy and thus, plays a backhand, yet, rather pivotal role in shaping many galactic properties, some of which are also readily observable. Observing the multi-phase CGM (via spectral-line ion measurements), however, remains a non-trivial effort even today. Low particle densities as well as the CGM’s vast spatial extent, coupled with likely deviations from a spherical distribution, marr the possibility of obtaining complete, unbiased, high-quality spectral information tracing the full extent of the gaseous halo. This often incomplete information leads to multiple inferences about the CGM properties that give rise to multiple contradicting models. In this regard, computer simulations offer a neat solution towards testing and, subsequently, falsifying many of these existing CGM models. Thanks to their controlled environments, simulations are able to not only effortlessly transcend several orders of magnitude in time and space, but also get around many of the observational limitations and provide some unique views on many CGM properties. In this thesis, I focus on effectively using different computer simulations to understand the role of CGM in various astrophysical contexts, namely, the effect of Local Group (LG) environment, major merger events and satellite galaxies. In Chapter 2, I discuss the approach used for modeling various phases of the simulated z = 0 LG CGM in Hestia constrained simulations. Each of the three realizations contain a Milky Way (MW)–Andromeda (M31) galaxy pair, along with their corresponding sets of satellite galaxies, all embedded within the larger cosmological context. For characterizing the different temperature–density phases within the CGM, I model five tracer ions with cloudy ionization modeling. The cold and cool–ionized CGM (H i and Si iii respectively) in Hestia is very clumpy and distributed close to the galactic centers, while the warm-hot and hot CGM (O vi, O vii and O viii) is tenuous and volume-filling. On comparing the H i and Si iii column densities for the simulated M31 with observational measurements from Project AMIGA survey and other low-z galaxies, I found that Hestia galaxies produced less gas in the outer CGM, unlike observations. My carefully designed observational bias model subsequently revealed the possibility that some MW gas clouds might be incorrectly associated with the M31 CGM in observations, and hence, may be partly responsible for giving rise to the detected mismatch between simulated data and observations. In Chapter 3, I present results from four zoom–in, major merger, gas–rich simulations and the subsequent role of the gas, originally situated in the CGM, in influencing some of the galactic observables. The progenitor parameters are selected such that the post–merger remnants are MW–mass galaxies. We generally see a very clear gas bridge joining the merging galaxies in case of multiple passage mergers while such a bridge is mostly absent when a direct collision occurs. On the basis of particle–to–galaxy distance computations and tracer particle analysis, I found that about 33–48 percent of the cold gas contributing to the merger–induced star formation in the bridge originated from the CGM regions. In Chapter 4, I used a sample of 234 MW-mass, L* galaxies from the TNG50 cosmological simulations, with an aim of characterizing the impact of their global satellite populations on the extended cold CGM properties of their host L* halos. On the basis of halo mass and number of satellite galaxies (N_sats ), I categorized the sample into low and high mass bins, and subsequently into bottom, inter and top quartiles respectively. After confirming that satellites indeed influence the extended cold halo gas density profiles of the host galaxies, I investigated the effects of different satellite population parameters on the host halo cold CGMs. My analysis showed that there is hardly any cold gas associated with the satellite population of the lowest mass halos. The stellar mass of the most massive satellite (M_*mms ) impacted the cold gas in low mass bin halos the most, while N_sats (followed by M_*mms ) was the most influential factor for the high mass halos. In any case, how easily cold gas was stripped off the most massive satellite did not play much role. The number of massive (Stellar mass, M* > 10^8 M_solar) satellites as well as the M_*mms associated with a galaxy are two of the most crucial parameters determining how much cold gas ultimately finds its way from the satellites to the host halo. Low mass galaxies are found rather lacking on both these fronts unlike their high mass counterparts. This work highlights some aspects of the complex gas physics that constitute the basic essence of a low-z CGM. My analysis proved the importance of a cosmological environment, local surroundings and merger history in defining some key observable properties of a galactic CGM. Furthermore, I found that different satellite properties were responsible for affecting the cold–dense CGM of the low and high-mass parent galaxies. Finally, the LG emerged as an exciting prospect for testing and pinning down several intricate details about the CGM.
Enacted in 2009, the National Policy on Climate Change (PNMC) is a milestone in the institutionalisation of climate action in Brazil. It sets greenhouse gas (GHG) emission reduction targets and a set of principles and directives that are intended to lay the foundations for a cross-sectoral and multilevel climate policy in the country. However, after more than a decade since its establishment, the PNMC has experienced several obstacles related to its governance, such as coordination, planning and implementation issues. All of these issues pose threats to the effectiveness of GHG mitigation actions in the country.
By looking at the intragovernmental and intergovernmental relationships that have taken place during the lifetime of the PNMC and its sectoral plans on agriculture (the Sectoral Plan for Mitigation and Adaptation to Climate Change for the Consolidation of a Low-Carbon Economy in Agriculture [ABC Plan]), transport and urban mobility (the Sectoral Plan for Transportation and Urban Mobility for Mitigation and Adaption of Climate Change [PSTM]), this exploratory qualitative research investigates the Brazilian climate change governance guided by the following relevant questions: how are climate policy arrangements organised and coordinated among governmental actors to mitigate GHG emissions in Brazil? What might be the reasons behind how such arrangements are established? What are the predominant governance gaps of the different GHG mitigation actions examined? Why do these governance gaps occur?
Theoretically grounded in the literature on multilevel governance and coordination of public policies, this study employs a novel analytical framework that aims to identify and discuss the occurrence of four types of governance gaps (i.e. politics, institutions and processes, resources and information) in the three GHG mitigation actions (cases) examined (i.e. the PNMC, ABC Plan and PSTM). The research results are twofold. First, they reveal that Brazil has struggled to organise and coordinate governmental actors from different policy constituencies and different levels of government in the implementation of the GHG mitigation actions examined. Moreover, climate policymaking has mostly been influenced by the Ministry of Environment (MMA) overlooking the multilevel and cross-sectoral approaches required for a country’s climate policy to mitigate and adapt to climate change, especially if it is considered an economy-wide Nationally Determined Contribution (NDC), as the Brazilian one is.
Second, the study identifies a greater manifestation of gaps in politics (e.g. lack of political will in supporting climate action), institutions and processes (e.g. failures in the design of institutions and policy instruments, coordination and monitoring flaws, and difficulties in building climate federalism) in all cases studied. It also identifies that there have been important advances in the production of data and information for decision-making and, to a lesser extent, in the allocation of technical and financial resources in the cases studied; however, it is necessary to highlight the limitation of these improvements due to turf wars, a low willingness to share information among federal government players, a reduced volume of financial resources and an unequal distribution of capacities among the federal ministries and among the three levels of government.
A relevant finding is that these gaps tend to be explained by a combination of general and sectoral set aspects. Regarding the general aspects, which are common to all cases examined, the following can be mentioned: i) unbalanced policy capabilities existing among the different levels of government, ii) a limited (bureaucratic) practice to produce a positive coordination mode within cross-sectoral policies, iii) the socioeconomic inequalities that affect the way different governments and economic sectors perceive the climate issue (selective perception) and iv) the reduced dialogue between national and subnational governments on the climate agenda (poor climate federalism). The following sectoral aspects can be mentioned: i) the presence of path dependencies that make the adoption of transformative actions harder and ii) the absence of perceived co-benefits that the climate agenda can bring to each economic sector (e.g. reputational gains, climate protection and access to climate financial markets).
By addressing the theoretical and practical implications of the results, this research provides key insights to tackle the governance gaps identified and to help Brazil pave the way to achieving its NDCs and net-zero targets. At the theoretical level, this research and the current country’s GHG emissions profile suggest that the Brazilian climate policy is embedded in a cross-sectoral and multilevel arena, which requires the effective involvement of different levels of political and bureaucratic powers and the consideration of the country’s socioeconomic differences. Thus, the research argues that future improvements of the Brazilian climate policy and its governance setting must frame climate policy as an economic development agenda, the ramifications of which go beyond the environmental sector. An initial consequence of this new perspective may be a shift in the political and technical leadership from the MMA to the institutions of the centre of government (Executive Office of the President of Brazil) and those in charge of the country’s economic policy (Ministry of Economy). This change could provide greater capacity for coordination, integration and enforcement as well as for addressing certain expected gaps (e.g. financial and technical resources). It could also lead to greater political prioritisation of the agenda at the highest levels of government. Moreover, this shift of the institutional locus could contribute to greater harmonisation between domestic development priorities and international climate politics. Finally, the research also suggests that this approach would reduce bureaucratic elitism currently in place due to climate policy being managed by Brazilian governmental institutions, which is still a theme of a few ministries and a reason for the occurrence of turf wars.
The first part of the thesis studies the properties of fast mode in magneto hydro-dynamic (MHD) turbulence. 1D and 3D numerical simulations are carried out to generate decaying fast mode MHD turbulence. The injection of waves are carried out in a collinear and isotropic fashion to generate fast mode turbulence. The properties of fast mode turbulence are analyzed by studying their energy spectral density, 2D structure functions and energy decay/cascade time. The injection wave vector is varied to study the dependence of the above properties on the injection wave vectors. The 1D energy spectrum obtained for the velocity and magnetic fields has 𝐸 (𝑘) ∝ 𝑘−2. The 2D energy spectrum and 2D structure functions in parallel and perpendicular directions shows that fast mode turbulence generated is isotropic in nature. The cascade/decay rate of fast mode MHD turbulence is proportional to 𝑘−0.5 for different kinds of wave vector injection. Simulations are also carried out in 1D and 3D to compare balanced and imbalanced turbulence. The results obtained shows that while 1D imbalanced turbulence decays faster than 1D balanced turbulence, there is no difference in the decay of 3D balanced and imbalanced turbulence for the current resolution of 512 grid points.
"The second part of the thesis studies cosmic ray (CR) transport in driven MHD turbulence and is strongly dependent on it’s properties. Test particle simulations are carried out to study CR interaction with both total MHD turbulence and decomposed MHD modes. The spatial diffusion coefficients and the pitch angle scattering diffusion coefficients are calculated from the test particle trajectories in turbulence. The results confirms that the fast modes dominate the CR propagation, whereas Alfvén, slow modes are much less efficient with similar pitch angle scattering rates. The cross field transport on large and small scales are investigated next. On large/global scales, normal diffusion is observed and the diffusion coefficient is suppressed by 𝑀𝜁𝐴 compared to the parallel diffusion coefficients, with 𝜁 closer to 4 in Alfvén modes than that in total turbulence as theoretically expected. For the CR transport on scales smaller than the turbulence injection scale 𝐿, both the local and global magnetic reference frames are adopted. Super diffusion is observed on such small scales in all the cases. Particularly, CR transport in Alfvén modes show clear Richardson diffusion in the local reference frame. The diffusion transition smoothly from the Richardson’s one with index 1.5 to normal diffusion as particle’s mean free path decreases from 𝜆∥ ≫ 𝐿 to 𝜆∥ ≪ 𝐿. These results have broad applications to CRs in various astrophysical environments".
With the implementation of intense, short pulsed light sources throughout the last years, the powerful technique of resonant inelastic X-ray scattering (RIXS) became feasible for a wide range of experiments within femtosecond dynamics in correlated materials and molecules.
In this thesis I investigate the potential to bring RIXS into the fluence regime of nonlinear X-ray-matter interactions, especially focusing on the impact of stimulated scattering on RIXS in transition metal systems in a transmission spectroscopy geometry around transition metal L-edges.
After presenting the RIXS toolbox and the capabilities of free electron laser light sources for ultrafast intense X-ray experiments, the thesis explores an experiment designed to understand the impact of stimulated scattering on diffraction and direct beam transmission spectroscopy on a CoPd multilayer system. The experiments require short X-ray pulses that can only be generated at free electron lasers (FEL). Here the pulses are not only short, but also very intense, which opens the door to nonlinear X-ray-matter interactions. In the second part of this thesis, we investigate observations in the nonlinear interaction regime, look at potential difficulties for classic spectroscopy and investigate possibilities to enhance the RIXS through stimulated scattering. Here, a study on stimulated RIXS is presented, where we investigate the light field intensity dependent CoPd demagnetization in transmission as well as scattering geometry. Thereby we show the first direct observation of stimulated RIXS as well as light field induced nonlinear effects,
namely the breakdown of scattering intensity and the increase in sample transmittance. The topic is of ongoing interest and will just increase in relevance as more free electron lasers are planned and the number of experiments at such light sources will continue to increase in the near future.
Finally we present a discussion on the accessibility of small DOS shifts in the absorption-band of transition metal complexes through stimulated resonant X-ray scattering. As these shifts occur for example in surface states this finding could expand the experimental selectivity of NEXAFS and RIXS to the detectability of surface states. We show how stimulation can indeed enhance the visibility of DOS shifts through the detection of stimulated spectral shifts and enhancements in this theoretical study. We also forecast the observation of stimulated enhancements in resonant excitation experiments at FEL sources in systems with a high density of states just below the Fermi edge and in systems with an occupied to unoccupied DOS ratio in the valence band above 1.
Potato FLC-like and SVP-like proteins jointly control growth and distinct developmental processes
(2023)
Based on worldwide consumption, Solanum tuberosum L. (potato) is the most important non-grain food crop. Potato has two ways of stable propagation: sexually via flowering and vegetatively via tuberization. Remarkably, these two developmental processes are controlled by similar molecular regulators and mechanisms. Given that FLC and SVP genes act as key flowering regulators in the model species Arabidopsis and in various other crop species, this study aimed at identifying FLC and SVP homologs in potato and investigating their roles in the regulation of plant development, with a particular focus on flowering and tuberization. Our analysis demonstrated that there are five FLC-like and three SVP like proteins encoded in the potato genome. The expression profiles of StFLCs and StSVPs throughout potato development and the detected interactions between their proteins indicate tissue specificity of the individual genes and distinct roles of a variety of putative protein complexes. In particular, we discovered that StFLC-D, as well as StFLC-B, StSVP-A, and StSVP-B play a complex role in the regulation of flowering time, as not only increased but also decreased levels of their transcripts promote earlier flowering. Most importantly, StFLC-D has a marked impact on tuberization under non-inductive conditions and susceptibility to temperature-induced tuber malformation, also known as second growth. Plants with decreased levels of StFLC-D demonstrated a strong ability to produce tubers under long days and appeared to be insensitive to temperature-induced second growth. Lastly, our data also suggests that StFLCs and StSVPs may be involved in the nitrogen-dependent regulation of potato development. Taken together, this study highlights the functional importance of StFLC and StSVP genes in the regulation of distinct developmental processes in potato.
Negotiations are a way of joint decision-making and thereby a form of social conflict. By determining the concrete allocation of scarce resources, negotiations have a great impact on the value creation of companies. If companies succeed in achieving better negotiation results in the long term, they can increase their profitability. Ensuring a company's negotiation success is therefore an organizational issue of central importance. While the question of ensuring individual negotiation success has been the subject and topic of multidisciplinary research for a long time, the question of how organizations can implement and ensure continuous negotiation success remains largely unexplored. This dissertation therefore aims to investigate how companies enable their employees to consistently achieve better negotiation outcomes. It is significant that, in the corporate context, negotiators do not act as individuals but as embedded representatives of an organization, and that negotiations are not one-time events but recurring necessities for the existence of the organization instead. In organizations, those recurring processes with a similar fundamental structure are handled by routines. A planned improvement of routines is often forced by new artifacts. In this context, artifacts refer to human-created technologies with which humans interact within routines and therefore artifacts have a central influence on executing the routine. If negotiation activities in companies are represented by organizational routines, one central issue for improving companies’ negotiation performance is the artifacts’ incorporation into organizational negotiation routines that facilitate the efficient application of the insights from negotiation research. The dissertation consists of three studies that were written as research papers to examine artifacts in the organizational negotiation context. The first study focuses on the pre-negotiation stage and presents four tools to assist negotiation practitioners in efficiently preparing for negotiation. The study examines the negotiation preparation’s effectiveness and efficiency and the negotiation outcome in a case-based experiment. The second study is devoted to a closer examination of the barriers that inhibit the adoption of negotiation support systems (NSSs) as one kind of organizational negotiation artifact. The investigation is conducted using a structural equation model based on information from participating practitioners. The third study is concerned with the future of negotiation support system research. An exploratory study based on qualitative in-depth interviews with proven and published experts in the field aims to evaluate the current state of research. The general discussion of the dissertation connects, summarizes, and concludes the study results and derives implications for practice, limitations, and future research ideas.
This research investigated the relationship between frequent engagement in industrial action (also known as ‘employee strikes’) and the internal attractiveness of government employment. It focused on a special group of public employees: public university lecturers and public-school teachers in Uganda who frequently engaged in industrial action. At the very basic level, the research explored whether public employees frequently engaged in industrial action because they considered public service employment to be unattractive or whether frequent engagement in industrial action was in fact part of the attractiveness of government employment. Beyond exploring these relationships, it also explained why (or why not) such relationships existed.
Methodologically, the research was conducted using an exploratory sequential design – a mixed methods study design that starts with a qualitative followed by a quantitative phase. It is the results of the initial qualitative phase that determined the direction of the subsequent quantitative phase. The qualitative phase started with an exploration of the relationship between industrial action and internal public service attractiveness, resulting into two specific research questions:
1) Why do public employees engage in industrial action and what role does frequent engagement in industrial action play in their perception of public service attractiveness?
2) Why and how is organizational justice related to public employees’ perception of public service attractiveness?
The above questions were answered both qualitatively and quantitatively. The theoretical postulations of the Social Movements Theories, Social Exchange Theory, and the Signaling Theory were used to structure the research assumptions and hypotheses.
The results showed that public employees engaged in industrial action mostly because of relative, rather than absolute deprivation. An established culture of workplace militancy was also found to be key in actualizing industrial action as was the (perceived) absence of alternatives to achieve workplace justice. Importantly, there was a clear dichotomy between absolute working conditions and frequent engagement in industrial action. Frequent engagement in industrial action was itself found to have both positive and negative effects on internal public service attractiveness. It was also found that public service attractiveness from the perspective of current public employees might be different from what it is from the perspective of prospective employees. This is because current public employees do not assume what it feels like to work for government, but mostly use their day-to-day lived experiences to judge the attractiveness of their employer. The existing literature is particularly deficient on analyzing public service attractiveness from an internal perspective, which is surprising given the public sector’s high reliance on internal recruitment.
The research results underlined key implications for theory, practice, and research. At theory level, the results suggested that public employee ratings of internal public service attractiveness were heavily affected by halo effects and should therefore not be taken at face value. The complex workplace social exchanges which are deeply rooted in organizational justice and the ‘personification metaphor’ were also emphasized. From an empirical perspective, the results underlined the need to prioritize internal public service attractiveness as recent research has confirmed the value of family socialization and internal recommendations in making public sector employment attractive, even to external applicants. This research argues that the centrality of organizational justice in public sector employee relations requires public sector organizations to be intentional in their bid to create fair, just, and attractive workplaces. Beyond assessing the fairness of personnel policies, procedures, and interactional relationships, it is also important to prepare and equip public managers with the right skills to promote and practice justice in their day-to-day interactions with public employees, and to encourage, improve, and facilitate alternative public employee feedback mechanisms.
Accurately solving classification problems nowadays is likely to be the most relevant machine learning task. Binary classification separating two classes only is algorithmically simpler but has fewer potential applications as many real-world problems are multi-class. On the reverse, separating only a subset of classes simplifies the classification task. Even though existing multi-class machine learning algorithms are very flexible regarding the number of classes, they assume that the target set Y is fixed and cannot be restricted once the training is finished. On the other hand, existing state-of-the-art production environments are becoming increasingly interconnected with the advance of Industry 4.0 and related technologies such that additional information can simplify the respective classification problems. In light of this, the main aim of this thesis is to introduce dynamic classification that generalizes multi-class classification such that the target class set can be restricted arbitrarily to a non-empty class subset M of Y at any time between two consecutive predictions.
This task is solved by a combination of two algorithmic approaches. First, classifier calibration, which transforms predictions into posterior probability estimates that are intended to be well calibrated. The analysis provided focuses on monotonic calibration and in particular corrects wrong statements that appeared in the literature. It also reveals that bin-based evaluation metrics, which became popular in recent years, are unjustified and should not be used at all. Next, the validity of Platt scaling, which is the most relevant parametric calibration approach, is analyzed in depth. In particular, its optimality for classifier predictions distributed according to four different families of probability distributions as well its equivalence with Beta calibration up to a sigmoidal preprocessing are proven. For non-monotonic calibration, extended variants on kernel density estimation and the ensemble method EKDE are introduced. Finally, the calibration techniques are evaluated using a simulation study with complete information as well as on a selection of 46 real-world data sets.
Building on this, classifier calibration is applied as part of decomposition-based classification that aims to reduce multi-class problems to simpler (usually binary) prediction tasks. For the involved fusing step performed at prediction time, a new approach based on evidence theory is presented that uses classifier calibration to model mass functions. This allows the analysis of decomposition-based classification against a strictly formal background and to prove closed-form equations for the overall combinations. Furthermore, the same formalism leads to a consistent integration of dynamic class information, yielding a theoretically justified and computationally tractable dynamic classification model. The insights gained from this modeling are combined with pairwise coupling, which is one of the most relevant reduction-based classification approaches, such that all individual predictions are combined with a weight. This not only generalizes existing works on pairwise coupling but also enables the integration of dynamic class information.
Lastly, a thorough empirical study is performed that compares all newly introduced approaches to existing state-of-the-art techniques. For this, evaluation metrics for dynamic classification are introduced that depend on corresponding sampling strategies. Thereafter, these are applied during a three-part evaluation. First, support vector machines and random forests are applied on 26 data sets from the UCI Machine Learning Repository. Second, two state-of-the-art deep neural networks are evaluated on five benchmark data sets from a relatively recent reference work. Here, computationally feasible strategies to apply the presented algorithms in combination with large-scale models are particularly relevant because a naive application is computationally intractable. Finally, reference data from a real-world process allowing the inclusion of dynamic class information are collected and evaluated. The results show that in combination with support vector machines and random forests, pairwise coupling approaches yield the best results, while in combination with deep neural networks, differences between the different approaches are mostly small to negligible. Most importantly, all results empirically confirm that dynamic classification succeeds in improving the respective prediction accuracies. Therefore, it is crucial to pass dynamic class information in respective applications, which requires an appropriate digital infrastructure.
The global climate crisis is significantly contributing to changing ecosystems, loss of biodiversity and is putting numerous species on the verge of extinction. In principle, many species are able to adapt to changing conditions or shift their habitats to more suitable regions. However, change is progressing faster than some species can adjust, or potential adaptation is blocked and disrupted by direct and indirect human action. Unsustainable anthropogenic land use in particular is one of the driving factors, besides global heating, for these ecologically critical developments. Precisely because land use is anthropogenic, it is also a factor that could be quickly and immediately corrected by human action.
In this thesis, I therefore assess the impact of three climate change scenarios of increasing intensity in combination with differently scheduled mowing regimes on the long-term development and dispersal success of insects in Northwest German grasslands. The large marsh grasshopper (LMG, Stethophyma grossum, Linné 1758) is used as a species of reference for the analyses. It inhabits wet meadows and marshes and has a limited, yet fairly good ability to disperse. Mowing and climate conditions affect the development and mortality of the LMG differently depending on its life stage.
The specifically developed simulation model HiLEG (High-resolution Large Environmental
Gradient) serves as a tool for investigating and projecting viability and dispersal success under different climate conditions and land use scenarios. It is a spatially explicit, stage- and cohort-based model that can be individually configured to represent the life cycle and characteristics of terrestrial insect species, as well as high-resolution environmental data and the occurrence of external disturbances. HiLEG is a freely available and adjustable software that can be used to support conservation planning in cultivated grasslands.
In the three case studies of this thesis, I explore various aspects related to the structure of simulation models per se, their importance in conservation planning in general, and insights regarding the LMG in particular. It became apparent that the detailed resolution of model processes and components is crucial to project the long-term effect of spatially and temporally confined events. Taking into account conservation measures at the regional level has further proven relevant, especially in light of the climate crisis. I found that the LMG is benefiting from global warming in principle, but continues to be constrained by harmful mowing regimes. Land use measures could, however, be adapted in such a way that they allow the expansion and establishment of the LMG without overly affecting agricultural yields.
Overall, simulation models like HiLEG can make an important contribution and add value
to conservation planning and policy-making. Properly used, simulation results shed light
on aspects that might be overlooked by subjective judgment and the experience of individual stakeholders. Even though it is in the nature of models that they are subject to limitations and only represent fragments of reality, this should not keep stakeholders from using them, as long as these limitations are clearly communicated. Similar to HiLEG, models could further be designed in such a way that not only the parameterization can be adjusted as required, but also the implementation itself can be improved and changed as desired. This openness and flexibility should become more widespread in the development of simulation models.
The relevance of physical fitness for children’s and adolescents’ health is indisputable and it is crucial to regularly assess and evaluate children’s and adolescents’ individual physical fitness development to detect potential negative health consequences in time. Physical fitness tests are easy-to-administer, reliable, and valid which is why they should be widely used to provide information on performance development and health status of children and adolescents. When talking about development of physical fitness, two perspectives can be distinguished. One perspective is how the physical fitness status of children and adolescents changed / developed over the past decades (i.e., secular trends). The other perspective covers the analyses how physical fitness develops with increasing age due to growth and maturation processes. Although, the development of children’s and adolescents’ physical fitness has been extensively described and analyzed in the literature, still some questions remain to be uncovered that will be addressed in the present doctoral thesis.
Previous systematic reviews and meta-analyses have examined secular trends in children’s and adolescents’ physical fitness. However, considering that those analyses are by now 15 years old and that updates are available only to limited components of physical fitness, it is time to re-analyze the literature and examine secular trends for selected components of physical fitness (i.e., cardiorespiratory endurance, muscle strength, proxies of muscle power, and speed). Fur-thermore, the available studies on children’s development of physical fitness as well as the ef-fects of moderating variables such as age and sex have been investigated within a long-term ontogenetic perspective. However, the effects of age and sex in the transition from pre-puberty to puberty in the ninth year of life using a short-term ontogenetic perspective and the effect of timing of school enrollment on children’s development of physical fitness have not been clearly identified. Therefore, the present doctoral thesis seeks to complement the knowledge of children’s and adolescents’ physical fitness development by updating secular trend analysis in selected components of physical fitness, by examining short-term ontogenetic cross-sectional developmental differences in children`s physical fitness, and by comparing physical fitness of older- and younger-than-keyage children versus keyage-children. These findings provide valuable information about children’s and adolescents’ physical fitness development to help prevent potential deficits in physical fitness as early as possible and consequently ensure a holistic development and a lifelong healthy life.
Initially, a systematic review to provide an ‘update’ on secular trends in selected components of physical fitness (i.e., cardiorespiratory endurance, relative muscle strength, proxies of muscle power, speed) in children and adolescents aged 6 to 18 years was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement guidelines. To examine short-term ontogenetic cross-sectional developmental differences and to compare physical fitness of older- and younger-than-keyage children versus keyage-children physical fitness data of 108,295 keyage-children (i.e., aged 8.00 to 8.99 years), 2,586 younger-than-keyage children (i.e., aged 7.00 to 7.99 years), and 26,540 older-than-keyage children (i.e., aged 9.00 to 9.99 years) from the third grade were analyzed. Physical fitness was assessed through the EMOTIKON test battery measuring cardiorespiratory endurance (i.e., 6-min-run test), coordina-tion (i.e., star-run test), speed (i.e., 20-m linear sprint test), and proxies of lower (i.e., standing long jump test) and upper limbs (i.e., ball-push test) muscle power. Statistical inference was based on Linear Mixed Models.
Findings from the systematic review revealed a large initial improvement and an equally large subsequent decline between 1986 and 2010 as well as a stabilization between 2010 and 2015 in cardiorespiratory endurance, a general trend towards a small improvement in relative muscle strength from 1972 to 2015, an overall small negative quadratic trend for proxies of muscle power from 1972 to 2015, and a small-to-medium improvement in speed from 2002 to 2015. Findings from the cross-sectional studies showed that even in a single prepubertal year of life (i.e., ninth year) physical fitness performance develops linearly with increasing chronological age, boys showed better performances than girls in all physical fitness components, and the components varied in the size of sex and age effects. Furthermore, findings revealed that older-than-keyage children showed poorer performance in physical fitness compared to keyage-children, older-than-keyage girls showed better performances than older-than-keyage boys, and younger-than-keyage children outperformed keyage-children.
Due to the varying secular trends in physical fitness, it is recommended to promote initiatives for physical activity and physical fitness for children and adolescents to prevent adverse effects on health and well-being. More precisely, public health initiatives should specifically consider exercising cardiorespiratory endurance and muscle strength because both components showed strong positive associations with markers of health. Furthermore, the findings implied that physical education teachers, coaches, or researchers can utilize a proportional adjustment to individually interpret physical fitness of prepubertal school-aged children. Special attention should be given to the promotion of physical fitness of older-than-keyage children because they showed poorer performance in physical fitness than keyage-children. Therefore, it is necessary to specifically consider this group and provide additional health and fitness programs to reduce their deficits in physical fitness experienced during prior years to guarantee a holistic development.
Personal data privacy is considered to be a fundamental right. It forms a part of our highest ethical standards and is anchored in legislation and various best practices from the technical perspective. Yet, protecting against personal data exposure is a challenging problem from the perspective of generating privacy-preserving datasets to support machine learning and data mining operations. The issue is further compounded by the fact that devices such as consumer wearables and sensors track user behaviours on such a fine-grained level, thereby accelerating the formation of multi-attribute and large-scale high-dimensional datasets.
In recent years, increasing news coverage regarding de-anonymisation incidents, including but not limited to the telecommunication, transportation, financial transaction, and healthcare sectors, have resulted in the exposure of sensitive private information. These incidents indicate that releasing privacy-preserving datasets requires serious consideration from the pre-processing perspective. A critical problem that appears in this regard is the time complexity issue in applying syntactic anonymisation methods, such as k-anonymity, l-diversity, or t-closeness to generating privacy-preserving data. Previous studies have shown that this problem is NP-hard.
This thesis focuses on large high-dimensional datasets as an example of a special case of data that is characteristically challenging to anonymise using syntactic methods. In essence, large high-dimensional data contains a proportionately large number of attributes in proportion to the population of attribute values. Applying standard syntactic data anonymisation approaches to generating privacy-preserving data based on such methods results in high information-loss, thereby rendering the data useless for analytics operations or in low privacy due to inferences based on the data when information loss is minimised.
We postulate that this problem can be resolved effectively by searching for and eliminating all the quasi-identifiers present in a high-dimensional dataset. Essentially, we quantify the privacy-preserving data sharing problem as the Find-QID problem.
Further, we show that despite the complex nature of absolute privacy, the discovery of QID can be achieved reliably for large datasets. The risk of private data exposure through inferences can be circumvented, and both can be practicably achieved without the need for high-performance computers.
For this purpose, we present, implement, and empirically assess both mathematical and engineering optimisation methods for a deterministic discovery of privacy-violating inferences. This includes a greedy search scheme by efficiently queuing QID candidates based on their tuple characteristics, projecting QIDs on Bayesian inferences, and countering Bayesian network’s state-space-explosion with an aggregation strategy taken from multigrid context and vectorised GPU acceleration. Part of this work showcases magnitudes of processing acceleration, particularly in high dimensions. We even achieve near real-time runtime for currently impractical applications. At the same time, we demonstrate how such contributions could be abused to de-anonymise Kristine A. and Cameron R. in a public Twitter dataset addressing the US Presidential Election 2020.
Finally, this work contributes, implements, and evaluates an extended and generalised version of the novel syntactic anonymisation methodology, attribute compartmentation. Attribute compartmentation promises sanitised datasets without remaining quasi-identifiers while minimising information loss. To prove its functionality in the real world, we partner with digital health experts to conduct a medical use case study. As part of the experiments, we illustrate that attribute compartmentation is suitable for everyday use and, as a positive side effect, even circumvents a common domain issue of base rate neglect.
Interested in the ideological workings of fiction, I study how major avant-garde tropes promote the potential of permanent renewal as white America’s property. Renewal ties to the capacities to create, progress, transcend, and simply be. From Black critique we know that, within dominant discourse, all these capacities have been denied to Black bodies ever since colonization. Black work has been fetishized, appropriated, stolen, and dismissed in and by dominant culture, while Black being is construed as negativity and barred on the level of ontology. It follows then that racialization operates on multiple levels in the conceptual frame of renewal. I study this conceptualization by re-reading the works of and criticism on progressive white authors. I examine how images of renewal enable the claim on futurity, transformative potential, and movement forward as exclusively white properties. Premised on oppositions between positive capacities and a state of complete incapacitation, these images are often viewed as separate constructions. This project shows that, deriving from white ideology, such representations are symbiotic and simultaneous - the "good" story of white renewal rests on the continual transgression towards Black being.
The present dissertation conducts empirical research on the relationship between urban life and its economic costs, especially for the environment. On the one hand, existing gaps in research on the influence of population density on air quality are closed and, on the other hand, innovative policy measures in the transport sector are examined that are intended to make metropolitan areas more sustainable. The focus is on air pollution, congestion and traffic accidents, which are important for general welfare issues and represent significant cost factors for urban life. They affect a significant proportion of the world's population. While 55% of the world's people already lived in cities in 2018, this share is expected to reach approximately 68% by 2050.
The four self-contained chapters of this thesis can be divided into two sections: Chapters 2 and 3 provide new causal insights into the complex interplay between urban structures and air pollution. Chapters 4 and 5 then examine policy measures to promote non-motorised transport and their influence on air quality as well as congestion and traffic accidents.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
Hantaviruses (HVs) are a group of zoonotic viruses that infect human beings primarily through aerosol transmission of rodent excreta and urine samplings. HVs are classified geographically into: Old World HVs (OWHVs) that are found in Europe and Asia, and New World HVs (NWHVs) that are observed in the Americas. These different strains can cause severe hantavirus diseases with pronounced renal syndrome or severe cardiopulmonary system distress. HVs can be extremely lethal, with NWHV infections reaching up to 40 % mortality rate. HVs are known to generate epidemic outbreaks in many parts of the world including Germany, which has seen periodic HV infections over the past decade. HV has a trisegmented genome. The small segment (S) encodes the nucleocapsid protein (NP), the middle segment (M) encodes the glycoproteins (GPs) Gn and Gc which forms up to tetramers and primarily monomers \& dimers upon independent expression respectively and large segment (L) encodes RNA dependent RNA polymerase (RdRp). Interactions between these viral proteins are crucial in providing mechanistic insights into HV virion development. Despite best efforts, there continues to be lack of quantification of these associations in living cells. This is required in developing the mechanistic models for HV viral assembly. This dissertation focuses on three key questions pertaining to the initial steps of virion formation that primarily involves the GPs and NP.
The research investigations in this work were completed using Fluorescence Correlation Spectroscopy (FCS) approaches. FCS is frequently used in assessing the biophysical features of bio-molecules including protein concentration and diffusion dynamics and circumvents the requirement of protein overexpression. FCS was primarily applied in this thesis to evaluate protein multimerization, at single cell resolution.
The first question addressed which GP spike formation model proposed by Hepojoki et al.(2010) appropriately describes the evidence in living cells. A novel in cellulo assay was developed to evaluate the amount of fluorescently labelled and unlabeled GPs upon co-expression. The results clearly showed that Gn and Gc initially formed a heterodimeric Gn:Gc subunit. This sub-unit then multimerizes with congruent Gn:Gc subunits to generate the final GP spike. Based on these interactions, models describing the formation of GP complex (with multiple GP spike subunits) were additionally developed.
HV GP assembly primarily takes place in the Golgi apparatus (GA) of infected cells. Interestingly, NWHV GPs are hypothesized to assemble at the plasma membrane (PM). This led to the second research question in this thesis, in which a systematic comparison between OWHV and NWHV GPs was conducted to validate this hypothesis. Surprisingly, GP localization at the PM was congruently observed with OWHV and NWHV GPs. Similar results were also discerned with OWHV and NWHV GP localization in the absence of cytoskeletal factors that regulate HV trafficking in cells.
The final question focused on quantifying the NP-GP interactions and understanding their influence of NP and GP multimerization. Gc mutlimers were detected in the presence of NP and complimented by the presence of localized regions of high NP-Gc interactions in the perinuclear region of living cells. Gc-CT domain was shown to influence NP-Gc associations. Gn, on the other hand, formed up to tetrameric complexes, independent from the presence of NP.
The results in this dissertation sheds light on the initial steps of HV virion formation by quantifying homo and heterotypic interactions involving NP and GPs, which otherwise are very difficult to perform. Finally, the in cellulo methodologies implemented in this work can be potentially extended to understand other key interactions involved in HV virus assembly.
Neue Wege ins Lehramt
(2023)
Bis zum Jahr 2035 fehlen nach neuesten Prognosen von Klemm (2022) in Deutschland ca. 127.000 Lehrkräfte. Diese große Lücke kann nicht mehr allein durch Lehrkräfte abge-deckt werden, die ein traditionelles Lehramtsstudium absolviert haben. Als Antwort auf den Lehrkräftemangel werden in Schulen in Deutschland daher vermehrt Personen ohne traditio-nelles Lehramtsstudium eingestellt, um die Unterrichtsversorgung zu gewährleisten (KMK, 2022). Nicht-traditionell ausgebildete Lehrkräfte durchlaufen vor ihrer Einstellung in den Schuldienst in der Regel ein alternatives Qualifizierungsprogramm. Diese Qualifizierungs-programme sind jedoch in ihrer zeitlichen und inhaltlichen Ausgestaltung sehr heterogen und setzen unterschiedliche Eingangsvoraussetzungen der Bewerber:innen voraus (Driesner & Arndt, 2020). Sie sind in der Regel jedoch deutlich kürzer als traditionelle Lehramtsstudien-gänge an Hochschulen und Universitäten, um einen schnellen Einstieg in den Schuldienst zu gewährleisten. Die kürzere Qualifizierung geht damit mit einer geringeren Anzahl an Lern- und Lehrgelegenheiten einher, wie sie in einem traditionellen Lehramtsstudium zu finden wäre. Infolgedessen kann davon ausgegangen werden, dass nicht-traditionell ausgebildete Lehrkräfte weniger gut auf die Anforderungen des Lehrberufs vorbereitet sind.
Diese Annahme wird auch oft in der Öffentlichkeit vertreten und die Kritik an alternati-ven Qualifizierungsprogrammen ist groß. So äußerte sich beispielsweise der Präsident des Deutschen Lehrerverbandes, Heinz-Peter Meidinger, im Jahr 2019 gegenüber der Zeitung „Die Welt“, dass die unzureichende Qualifizierung von Quereinsteiger:innen „ein Verbre-chen an den Kindern“ sei (Die Welt, 2019). Die Forschung im deutschsprachigen Raum, die in der Läge wäre, belastbare Befunde für die Unterstützung dieser Kritik liefern zu können, steht jedoch noch am Anfang. Erste Arbeiten weisen generell auf wenige Unterschiede zwi-schen traditionell und nicht-traditionell ausgebildeten Lehrkräften hin (Kleickmann & An-ders, 2011; Kunina-Habenicht et al., 2013; Oettinghaus, Lamprecht & Korneck, 2014). Ar-beiten, die Unterschiede finden, zeigen diese vor allem im Bereich des pädagogischen Wis-sens zuungunsten der nicht-traditionell ausgebildeten Lehrkräfte. Die Frage nach weiteren Unterschieden, beispielsweise in der Unterrichtsqualität oder im beruflichen Wohlbefinden, ist bislang jedoch für den deutschen Kontext nicht beantwortet worden.
Die vorliegende Arbeit hat zum Ziel, einen Teil dieser Forschungslücken zu schließen. Sie bearbeitet in diesem Zusammenhang im Rahmen von drei Teilstudien die Fragen nach Unterschieden zwischen traditionell und nicht-traditionell ausgebildeten Lehrkräften hin-sichtlich ihrer professionellen Kompetenz, Berufswahlmotivation, Wohlbefinden und Unter-richtsqualität. Die übergeordnete Fragestellung wird vor dem Hintergrund des theoretischen Modells zu den Determinanten und Konsequenzen der professionellen Kompetenz (Kunter, Kleickmann, Klusmann & Richter, 2011) bearbeitet. Dieses Modell wird auch für die theore-tische Aufarbeitung der bereits bestehenden nationalen und internationalen Forschungsarbei-ten zu Unterschieden zwischen traditionell und nicht-traditionell ausgebildeten Lehrkräften herangezogen.
Teilstudie I untersucht zunächst Unterschiede in der professionellen Kompetenz zwi-schen traditionell und nicht-traditionell ausgebildeten Lehrkräften. Nach dem Kompetenz-modell nach Baumert und Kunter (2006) werden die beiden Gruppen in den vier Aspekten professioneller Kompetenz – Professionswissen, Überzeugungen, motivationale Orientierun-gen und selbstregulative Fähigkeiten – verglichen. Im Fokus dieser Arbeit stehen traditionell ausgebildete Lehramtsanwärter:innen und die sogenannten Quereinsteiger:innen während des Vorbereitungsdiensts. Mittels multivariater Kovarianzanalysen wurde eine Sekundärdaten-analyse des Projekts COACTIV-R durchgeführt und Unterschiede analysiert.
Teilstudie II beleuchtet sowohl Determinanten als auch Konsequenzen professioneller Kompetenz. Auf Seiten der Determinanten werden Unterschiede in der Berufswahlmotivati-on zwischen Lehrkräften mit und ohne traditionellem Lehramtsstudium untersucht. Ferner erfolgt die Analyse von Unterschieden im beruflichen Wohlbefinden (emotionale Erschöp-fung, Enthusiasmus) und die Intention, im Beruf zu verbleiben, als Konsequenz professionel-ler Kompetenz. Es erfolgte eine Analyse der Daten aus der Pilotierungsstudie aus dem Jahr 2019 für den Bildungstrend des Instituts für Qualitätsentwicklung im Bildungswesen (IQB). Unterschiede zwischen traditionell und nicht-traditionell ausgebildeten Lehrkräften wurden erneut mittels multivariater Kovarianzanalysen berechnet.
Abschließend erfolgte in Teilstudie III die Untersuchung von Unterschieden in der Un-terrichtsqualität zwischen traditionell und nicht-traditionell ausgebildeten Lehrkräften als Konsequenz professioneller Kompetenz. Hierzu wurden Daten des IQB-Bildungstrends 2018 im Rahmen einer Sekundäranalyse mithilfe doppelt-latenter Mehrebenenanalysen genutzt. Es wurden die Unterschiede in den Bereichen Abwesenheit von Störungen, kognitive Akti-vierung und Schüler:innenunterstützung betrachtet.
Im finalen Kapitel der vorliegenden Arbeiten werden die zentralen Befunde der drei Teilstudien zusammengefasst und diskutiert. Die Ergebnisse weisen darauf hin, dass sich traditionell und nicht-traditionell ausgebildete Lehrkräfte nur in wenigen der untersuchten Aspekte signifikant voneinander unterscheiden. Nicht-traditionell ausgebildete Lehrkräfte verfügen über weniger pädagogisches Wissen, haben bessere selbstregulative Fähigkeiten und unterscheiden sich nicht in ihren Berufswahlmotiven, ihrem Wohlbefinden und in der Unterrichtsqualität von traditionell ausgebildeten Lehrkräften. Die Ergebnisse öffnen die Tür für die Diskussion der Relevanz des traditionellen Lehramtsstudiums, bieten eine Grundlage bzgl. der Implikationen für weiterführende Forschungsarbeiten und die Bildungspolitik. Die Arbeiten werden abschließend hinsichtlich ihrer Grenzen bewertet.